We are what we eat - how diet is shaping our health
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Short talk at FoodMattersLive conference London Nov 2015
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We are what we eat - how diet is shaping our health
- 1. We are what we eat – insights from nutrigenomics research to understand how diet is shaping our health Michael Müller Professor of Nutrigenomics & Systems Nutrition Director of the NRP Food & Health Alliance Norwich Medical School @nutrigenomics
- 2. Outline of my talk One cannot change the genome but how to use it. The most potent genome challenges: exercise, fasting/CR, microbiome challenges & “healthy” nutrition. “Beneficial” commensal bacteria may behave less “beneficial” under the wrong circumstances. How to use this information for precision treatments or personalized nutrition.
- 3. “You are what you eat, have eaten & host”
- 4. 100 50 0 % Energy Low-fat meat Chicken Eggs Fish Fruits Vegetables (carrots) Nuts Honey 100 50 0 % Energy Fruits Vegetables Beans Meat Chicken Fish Grain Milk/-products Isolated Carbs Isolated Fat/Oil Alcohol 1.200.000 Generations between feast en famine Paleolithic era 3-4 Generations in energy abundance Modern Times Our “paleolithic” ‘hunter-gatherer’ genes + modern diets Real Foods with ‘challenges’ “Safe, processed” foods = Less challenges
- 5. No pain, no gain The molecular basis of adaptation
- 6. Transcriptional regulatory networks in positive and negative energy balance – why nutrition matters
- 7. Biological systems multi-omics Nature Reviews Genetics | AOP, published online 13 January 2015 Phenome • Metabolic Syndrome CVD NAFLD • Inflammatory Diseases • Prostate Cancer
- 8. The most powerful trigger next to exercise is ‘eating less’ Weight Gain Survival Age (weeks) Survival(%) 52 65 78 91 104 50 75 100 C CR MF INT * * ** Age (month) Bodyweight(g) 15 25 35 45 55 65 C CR MF INT 6 12 24 28
- 9. From local problems to systemic diseases – the contribution of the gut (microbiome)
- 10. Feed your gut
- 11. 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 AHR activation 11622_at Ahr Detoxification 13076_at Cyp1a1 14858_at Gsta2 14859_at Gsta3 14862_at Gstm1 18104_at Nqo1 Inflammation (ILCs and IELs) 19885_at Rorc (ILC) 12501_at Cd3e (IEL) 12502_at Cd3g (IEL) 12525_at Cd8a (IEL) 20302_at Ccl3 (IEL) 20304_at Ccl5 (IEL) 432729_at Tcrg-C (IEL) 17067_at Ly6c1 (IEL, type a) 16636_at Klra5 (IEL, type b) 12504_at Cd4 (T helper) 12475_at Cd14 (Monocytes) 12478_at Cd19 (B cells) HF-Chow HF-LF Chow-LF Different diets are leading to different gut phenotypes (small intestine) Dietary impact on the activation of the AhR essential for the gut immune system 3 Diets = 3 functional states of the gut
- 12. What is a healthy diet? "Eat food, not too much, mostly plants" Michael Pollan, The Omnivore's Dilemma
- 13. Anti-inflammatory effects of plant food components Tilg H, Moschen AR. Food, immunity, and the microbiome Gastroenterology. 2015 May;148(6):1107-19.
- 14. Role of dietary fibres on gut function in mice SCFA INULIN, FOS, GuarGum, NAXUS (Arabinoxylan), Resistant Starch, Control = Starch microbiota 10 days Lange K, Hugenholtz F, Jonathan MC, Schols HA, Kleerebezem M, Smidt H, Müller M, Hooiveld GJ. Mol Nutr Food Res. 2015, 59,1590–1602.
- 15. Integration of epithelial cell gene expression with luminal microbiota composition Bacterial groups within Clostridium cluster XIVa positively correlated with genes involved in energy metabolism (1) Lange K, Hugenholtz F, Jonathan MC, Schols HA, Kleerebezem M, Smidt H, Müller M, Hooiveld GJ. Mol Nutr Food Res. 2015, 59,1590–1602.
- 16. PPARg targets 1 Activation score per dietary fiber RS FOS AX IN GG PPARG 2.83 2.01 4.23 3.07 HNF4A 2.58 3.50 TP53 2.36 2.82 ATF4 2.61 2.43 PPARGC1A 2.39 2.08 XBP1 2.93 NR5A2 2.61 SREBF1 2.58 FOXC2 2.43 SREBF2 2.22 PTTG1 2.21 NR1I2 2.09 CEBPB 2.02 KDM5B 2.00 NCOA2 2.00 TP63 -2.15 STAT5B -2.16 MBD2 -2.23 STAT5A -2.36 MYC -2.63 Upstream regulator Role of Pparg in fibre-dependent gene regulation Fibre-specific effects on PPARy transcriptome Lange K, Hugenholtz F, Jonathan MC, Schols HA, Kleerebezem M, Smidt H, Müller M, Hooiveld GJ. Mol Nutr Food Res. 2015, 59,1590–1602.
- 17. Role of gut microbiota in heme induced stress • Consumption of red meat is associated with increased colorectal cancer risk. We show that the gut microbiota is pivotal in this increased risk. • Mice receiving a diet with heme, a proxy for red meat, show a damaged gut epithelium and a compensatory hyperproliferation that can lead to colon cancer. • Mice receiving heme together with antibiotics do not show this damage and hyperproliferation.
- 18. Proposed mechanism of how microbiota facilitates heme-induced compensatory hyperproliferation Noortje Ijssennagger et al. PNAS 2015;112:10038-10043
- 19. We are what we fed them…? ‘our gastrointestinal tract is not only the body's most under-appreciated organ, but "the brain's most important adviser”’.
- 20. Future Perspective: Stratification and precision treatments Identification and personalized treatments of patients at risk for developing type 2 diabetes based on their microbiota http://personalnutrition.org
- 21. Summary One cannot change the genome but the use of genome capacity => phenotype plasticity is an essential feature of health. The most potent genome challenges: exercise, fasting/CR, microbiome challenges & “healthy” nutrition. "Eat food, not too much, mostly plants”: many bioactive molecules. Transcription factors (e.g. PPARg, FXR, AHR or NRF2) are involved in host sensing mechanisms of microbial metabolites & food bioactives. “Beneficial” commensal bacteria may behave less “beneficial” under the wrong circumstances (e.g. dietary heme or other dietary stressors). Embrace challenges from young to old – with diverse foods & lifestyles that ‘mildly’ challenge the genome. Precision treatments of people at risk for developing non- communicable diseases based on genome/phenome data.
- 22. >2017 The Norwich Centre for Food and Health
Editor's Notes
- Anti-inflammatory effects of food components. (A) AhR provides an important link between the intestinal immune system and food-derived ligands. AhR activating ligands include indolo(3,2-b) carbazole or 6-formylindolo(3,2-b) carbazole, which come from cruciferous vegetables, flavonoids, and polyphenols, (B) as well as bacterial-derived molecules, such as phenazins and naphtoquinon phthiocol, and microbial metabolic products such as 1,4-dihydroxy-2-naphthoic acid. AhR ligands activate chaperone-bound AhRs, which dimerize with the AhR nuclear translocator (Arnt) to regulate gene expression. AhR signaling is required for the generation and maintenance of intestinal immune cells including specialized intraepithelial lymphocytes and CD4-RORγδ+ innate lymphoid cells. AhR-induced production of IL22 could have immunomodulatory and metabolic effects. (C) Tryptophan is another important anti-inflammatory molecule in food. Its uptake is regulated by intestinal ACE2 (independent of its functions in the renin-angiotensin system). Tryptophan is converted to indole-3-aldehyde (another ligand of AhR) by bacterial enzymes. Tryptophan is required for the generation of nicotinamide (also vitamin B3 or niacin). Nicotinamide can activate the mTOR pathway, including p70S6 kinase and antimicrobial peptides, to produce anti-inflammatory effects. Within the cell, tryptophan is converted to kynurenine (another AhR ligand) by indoleamine 2,3-dioxygenase (IDO). (D) Soluble dietary fiber (complex carbohydrates, CCH) is cleaved into SCFAs by bacterial glycoside hydrolases. The SCFAs acetate, proprionate, and butyrate have anti-inflammatory effects. SCFAs bind GPCRs such as GPR41, GPR43, or GPR109A, which activate the transcription factor arrestin-β2. Interestingly, GPCRs can be activated by other ligands such as niacin (GPR109A) and Ω-3 fatty acids (GPR120). Butyrate is a natural inhibitor of the histone deacetylases 6 and 9, and could promote development of peripheral regulatory T cells through epigenetic mechanisms. AA, amino acids; FOXP3, forkhead box P3; HA/Nam, nicotinamide; IE, intraepithelial; ILCs, intestinal lymphoid cells; mTOR, mechanistic target of rapamycin; Treg, regulatory T cells.
- Identification of upstream regulators The underlying mechanisms by which the fibers modulated gene expression changes are not well understood. We therefore aimed to identify potential upstream transcriptional regulators that could explain the observed shifts in gene expression profiles. Next to the canonical involvement of PPAR, the different diets appear to modulate gene sets that are connected to other regulators (Table 1).In line with results obtained by GSEA, PPAR, particularly the isoform PPARG, was potentially activated for FOS, AX, GG, but most for IN. In addition, we observed both overlapping and unique sets of PPARG target genes within the fiber specific GS (Supplemental Fig. 1). Next to PPARG, several other regulators were predicted to play a role in the transcriptional responses elicited by one or more of the fiber diets. Notably, the transcription regulator KDM5B was uniquely predicted to play a role in control of the RS modulated gene expression profiles, which may at least in part explain the specific gene expression profile induced by RS. KDM5B plays a role in cell fate decisions. In addition, within the FOS-specific transcription pattern changes, NR5A2 and MBD2 were uniquely predicted to play a role in the control of these genes. Among the transcriptional regulator for GG diets we identified sterol/lipid metabolism related regulator (SREBF1, SREBF2) and NR1I2 involved in drug metabolism. Taken together, we identified potential transcription regulators that may explain commonalities and differences in gene regulation patterns observed for the different fiber diets. In particular, PPARG is a potential important regulator involved in the gene expression response to dietary fiber in colonic epithelia.
- Proposed mechanism of how microbiota facilitates heme-induced compensatory hyperproliferation. (Upper) Processes when normal microbiota is present (i.e., without Abx) leading to compensatory hyperproliferation. (Lower) How Abx cause the mucus layer to be protective against cytotoxic micelles. R-S-S-R indicates native intra- and intermolecular disulfide bonds in the mucus that can be reduced by H2S to thiols (R-S-H) and trisulfides (R-S-S-S-R).
- Subjects may be identified to be at risk to develop T2D based on their microbiome. Different microbiome compositions, together with classical clinical biomarkers, may potentially allow stratification to different treatments/preventions such as lifestyle interventions (yellow), specific diets and/or prebiotics (red), classical or novel probiotics (blue), a combination of diet and probiotic (purple), specific drugs (green), or bariatric surgery (blue).